This Reference Manual was developed by a Measurement Systems Analysis Note: The approach used in the 4th Edition is to compare standard deviations. Title: Measurement Systems Analysis (MSA), 4th Edition approval is required for measurement systems analysis methods not covered in this manual. MSA 4th . Chapter III – Section B. Variable Measurement System Study - Guidelines. MSA ( Measurement Systems Analysis) 4 th. Edition Errata Sheet. Analysis of Results.

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compliant with AIAG MSA Manual - 4th Edition. Find out how Requirements ProMSA: Measurement Systems Analysis Software: AIAG MSA 4. Unformatted text preview: MEASUREMENT SYSTEMS ANALYSIS Reference Manual Fourth Edition i ii FOREWORD This Reference Manual was developed by. Measurement. Systems Analysis, Reference Manual. 4th ed., Michigan (USA). [2] ISO () ISO/DIS Statistical methods in process management

Run Chart by Part Gage Performance Curve Without Error X—Y Plot of Averages by Size List of Figures Figure I-A 1: Example of a Traceability Chain for a Length Measurement Relationships between Bias and Repeatability Dot diagram of h values Linearity Study — Graphical Analysis Actual Cp tolerance based Gage Performance Curve —Example Residual Plot Bias Study — Histogram of Bias Study Comparison X—Y Plots Control Chart Analysis for Stability Chapter I — Section A Introduction.

Purpose and Terminology 2.

For instance. In general. The quality of measurement data is defined by the statistical properties of Quality of multiple measurements obtained from a measurement system operating under stable conditions.

The data. Much of the variation in a set of measurements may be due to the interaction between the measurement system and its environment. Analytic studies are among the most important uses of measurement data because they lead ultimately to better understanding of processes. Another use of measurement data is to determine if a significant relationship exists between two or more variables.

The statistical properties most commonly used to characterize the quality of data are the bias and variance of the measurement system. Measurement operating under stable conditions. The benefit of using a data-based procedure is largely determined by the quality of the measurement data used.

Deming called analytic studies. One of the most common reasons for low-quality data is too much variation. Purpose and Terminology Introduction Measurement data are used more often and in more ways than ever before. To ensure that the benefit derived from using measurement data is great enough to warrant the cost of obtaining it.

For example. Studies that explore such relationships are examples of what Dr. The property called bias refers to the location of the data relative to a reference master value. Purpose and Terminology Section A Introduction. If the data quality is low. That possible relationship could be studied by using a statistical procedure called regression analysis to compare measurements of the critical dimension with measurements of the temperature of the feed material.

Eisenhart Much of the work of managing a measurement system is directed at monitoring and controlling variation. That makes interpreting the data more difficult and the measurement system. If the interaction generates too much variation.

It is recommended that competent statistical resources be consulted for more complex or unusual situations not discussed here. Although the guidelines are general enough to be used for any measurement system.

Purpose The purpose of this document is to present guidelines for assessing the quality of a measurement system. This section provides a summary of such terms which are used in this manual.

The process of assigning the numbers is defined as the measurement process. In that case. Among other things. In this document. Customer approval is required for measurement systems analysis methods not covered in this manual. Many of the analyses are useful with other types of measurement systems and the manual does contain references and suggestions.

MSA 4th.pdf - MEASUREMENT SYSTEMS ANALYSIS Reference Manual...

Terminology The discussion of the analysis of measurement system can become confusing and misleading without an established set of terms to refer to the common statistical properties and related elements of the measurement system.

This document is not intended to be a compendium of analyses for all measurement systems. Its primary focus is measurement systems where the readings can be replicated on each part. Purpose and Terminology measurement system used to measure the volume of liquid in a tank may be sensitive to the ambient temperature of the environment in which it is used.

Viewing a measurement system this way is useful because it allows us to bring to bear all the concepts. From these definitions it follows that a measurement process may be viewed as a manufacturing process that produces numbers data for its output. Section E for terminology definitions and discussion. ASTM E NIST Measurement works collaboratively with these other NMIs to assure measurements made Institutes in one country do not differ from those made in another.

Traceability Traceability is an important concept in the trade of goods and services. The traceability linkage of these consensus standards to the NMI may not always be clearly understood. Department of Commerce. One thing to note is that the capabilities of these NMIs will vary from country to country and not all types of measurements are compared on a regular basis.

This helps reduce the need for re-test. NIST provides these services directly to many types of industries. This is why it is important to understand to whom measurements are traceable and how traceable they are.

With the advancement in measurement technologies and the usage of state-of-the- art measurement systems in industry. Measurements that are traceable to the same or similar standards will agree more closely than those that are not traceable.

The calibration system determines measurement traceability to the measurement systems through the use of calibration methods and standards.

Calibration may also Systems include steps to detect. Traceability is the chain of calibration events originating with the calibration standards of appropriate metrological capability or measurement uncertainty. This is an acceptable and appropriate means of attaining traceability to NIST. This linkage or chain of events ultimately finds its way onto the factory floor and then provides the basis for measurement traceability. A calibration system is a set of operations that establish.

Each calibration event includes all of the elements necessary including standards. It is True Value desired that any individual reading be as close to this value as economically possible. Because the reference value is used as a surrogate for the true value. Measurement Assurance Programs MAPs can be used to verify the acceptability of the measurement processes used throughout the calibration system. Purpose and Terminology An organization may have an internal calibration laboratory or organization which controls and maintains the elements of the calibration events.

This usage is not recommended.

Independent measurements imply that the traceability of the secondary measurement process is derived from a separate chain of calibration events from those used for the initial measurement. When a qualified laboratory is not available for a given piece of equipment. MAPs may also include the use of statistical process control SPC to track the long-term stability of a measurement process.

When the calibration event is performed by an external. Purpose and Terminology A Tutorial by G. The 3 Portions of this chapter adapted with permission from Measurement Systems Analysis. Gruska and M. This activity. The Third Generation.

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Knowledge is gained of what the process is doing by evaluating the parameters or results of the process. But this examination activity is itself a process. Equipment was the major focus — the more "important" the characteristic. Each measurement would always agree with a standard. Management must therefore also provide clear operational definitions and standards as well as training and support. But it is the statistical properties of the data produced that determine the quality of the measurement system.

The measurement and analysis activity is a process — a measurement process. Data obtained from such a machine can be very useful for analyzing a manufacturing process. The owner of the process has. But downloading the best or the latest measurement technology will not necessarily guarantee correct production process control decisions.

Any and all of the management. Systems measurement systems with such desirable statistical properties seldom exist. This means that the customers and their needs must first be identified. Edwards Deming. Equipment is only one part of the measurement process. Statistical properties that are most important for one use are not necessarily the most important properties for another use.

Other properties. Management must provide the resources to download equipment which is necessary and sufficient to do this. The owner of the process must know how to correctly use this equipment and how to analyze and interpret the results.

The customer. The quality of a measurement system is usually determined solely by the statistical properties of the data it produces over time. Consequently these gages were often not used properly or simply not used. In order to control the measurement system variation: If so. To accomplish this. These sources of variation are due to Variation common and special causes. The statistical properties of the measurement system may change as the items being measured vary. Chapter I — Section B The Measurement Process Management has the responsibility for identifying the statistical properties that are the most important for the ultimate use of the data.

Assess the measurement system to the feature tolerance. Management is also responsible for ensuring that those properties are used as the basis for selecting a measurement system. Similar to all processes. FP6PF This means that under repeatable conditions. There are various methods of 6 The measurement analyst must always consider practical and statistical significance.

This can be referred to as statistical stability and is best evaluated by graphical methods. These include: Although each measurement system may be required to have different statistical properties. Although the specific causes will depend on the situation. This rule of thumb was intended as a practical minimum starting point for gage selection.

The increments of measure should be small relative to the process variation or specification limits for the purpose of measurement. The commonly known Rule of Tens. T 8 See Appendix F for an alternate error model.. This may be thought of as an error model for a E Environment complete measurement system. Since the actual sources of variation affecting a specific measurement system will be unique to that system.

I Instrument S. Chapter I — Section B The Measurement Process presenting and categorizing these sources of variation such as cause-effect diagrams. Figure I-B 1 displays a cause and effect diagram showing some of the potential sources of variation.

Mary Hoskins. S Standard The acronym S.

Measurement System Variability Cause and Effect Diagram mass build amplification elastic build tolerances robustness deformation cleanliness contact bias geometry elastic properties deformation adequate stability effects supporting datums features design validation consistency.

Readings vary from each other due to common and special causes. Another common scenario is the classification of parts into specific categories e. This adds stability and consistency to the measurement system capability. This does not restrict the application of the discussion to other categorization activities.

Philosophy Interest Product control Is the part in a specific category? Process control Is the process variation stable and acceptable? Table I-B1: Control Philosophy and Driving Interest Further classifications may be reworkable. It is the combination of errors quantified by linearity. Because the output of the measurement system is used in making a decision about the product and the process.

The effects of the various sources of variation on the measurement system should be evaluated over a short and long period of time.

For the rest of the discussion. The measurement system performance. This is accomplished by determining whether our process is in statistical control i. Under a product control philosophy this classification activity would be the primary reason for measuring a part..

The measurement system capability is the measurement system random error over a short period of time. In order to better understand the effect of measurement system error on Effect on product decisions. That is. Following that is a section which addresses its impact on the process decision.

RISK is the chance of making a decision which will be detrimental to an individual or process That is. Decisions A wrong decision will sometimes be made whenever any part of the above measurement distribution overlaps a specification limit. This gives three distinct areas: The impact on process decisions would be as follows: This discussion assumes that the measurement process is in statistical control and on target.

With process control. If either of these assumptions is violated then there is little confidence that any observed value would lead to a correct decision. The basic relationship between the actual and the observed process variation is: If the measurement system Cp index were itself 1. To reach a specific process capability goal would require factoring in the measurement variation. In reality 1. The most common situation involving the use of different instruments is the case where the instrument used at the supplier has higher order discrimination than the production instrument gage.

A worst case scenario would be if a production gage has not been qualified but is used. Oftentimes this involves some studies done on the equipment at the supplier's location and then at the customer's location. If the measurement system used at either location is not consistent with the measurement system that will be used under normal circumstances then confusion may ensue.

The difference in the observed Cp of 1. Without this knowledge. Deming used to describe the effects of tampering. Rule 2: Adjust the process in an equal amount and in an opposite direction from where the process was last measured to be. According to instructions the operator attempts to adjust the process up by. The operating instructions require the operator to verify the weight at setup and every hour based on one sample.

Over-adjustment of the process has added variation and will continue to do so. Rule 3: Reset the process to the target. Out of the Crisis. Massachusetts Institute of Technology. The setup instruction for the precious metal process is an example of Rule 3. Now the process is running at 5. This is one example of the funnel experiment that Dr.

When the operator checks the setup this time. At setup. Four rules of the funnel experiment are: Rule 1: Make no adjustment or take no action unless the process is unstable. If the part measured is off target. Then adjust the process in an equal amount and in an opposite direction from the target. Rule 4: Adjust the process to the point of the last measurement.

If the results are beyond the interval 4. Consider a situation where the weight of a precious metal coating on a part is being controlled to a target of 5. Rule 1 is the best choice to produce minimum variation. Rules 2. Deming referred to this type of Experiment measurement and decision-making as tampering. Rule 1 Simple standard measurement tools like micrometers or calipers may not require this in-depth strategy and planning. Another guide would be the level of tolerance assigned to a specific dimension.

Measurement Systems Analysis (MSA), 4th Edition

The type. Not all product and process characteristics require measurement systems whose development falls under this type of scrutiny.

Any measurement system may require more or less strategic planning and scrutiny depending on a given product or process situation. Common sense is the guide in any case. Simple measuring tools and devices i. Many decisions made during the planning stage could affect the direction and selection of measurement equipment.

A basic rule of thumb is whether the characteristic being measured on the component or sub-system has been identified in the control plan or is important in determining the acceptance of the product or process. The actual degree of involvement or implementation in many of the activities below should be driven by the particular measurement system..

The decision as to the appropriate level shall be left to the APQP team assigned to the measurement process and customer. In some cases due to the risk involved in the component being measured or because of the cost and complexity of the measurement device. What is the purpose and how will the measurement result be used?

The planning stage will set the course and have a significant effect on how well the measurement process operates and can reduce possible problems and measurement error in the future. The first step is to establish the purpose for the measurement and how the Identify the measurement will be utilized.

A cross-functional team organized early in the Purpose of the development of the measurement process is critical in accomplishing this task. The Measurement Life Cycle concept expresses the belief that the Measurement Life measurement methods may change over time as one learns and improves the Cycle process.

For example, measurement may start on a product characteristic to establish stability and capability of the process. This may lead to an understanding of critical process control characteristics that directly affect the part characteristics.

Dependency on part characteristic information becomes less and the sampling plan may be reduced to signify this understanding five parts per hour sample reduced to one part per shift. Also, the method of measurement may change from a CMM measurement, to some form of attribute gaging. Eventually it may be found that very little part monitoring may be required as long as the process is maintained or measuring and monitoring the maintenance and tooling may be all that is needed.

The level of measurement follows the level of process understanding. Most of the measuring and monitoring could eventually end up at suppliers of incoming material. The same measurement, on the same characteristic, at the same area of the process, over an extensive period of time is evidence of a lack of learning or a stagnant measurement process.

Before a measurement system can be downloadd, a detailed engineering Criteria for a concept of the measurement process is developed. Using the purpose Measurement developed above, a cross-functional team of individuals will develop a plan and concept for the measurement system required by the design.

Here are Process Design some guidelines: Selection The team needs to evaluate the design of the subsystem or component and identify important characteristics. These are based on customer requirements and the functionality of the subsystem or component to the total system.

If the important dimensions have been identified already, evaluate the ability to measure the characteristics. For example, if the important characteristic of a plastic injection molded component was on the mold parting line, the dimensional check would be difficult and measurement variation would be high.

One method to capture issues similar to these would be to use a FMEA process to analyze areas of risk in gage design both from an ability to measure to the part to the functionality gage Design and Process FMEA.

This would aid in the development of the maintenance and calibration plan. Develop a flow chart showing critical process steps in the manufacturing or assembly of the part or subsystem. Identify key inputs and outputs to each step in the process. This will aid in the development of the measurement equipment criteria and requirements affected by the location in the process. A measurement plan, a list of measurement types, comes out of this investigation. For complex measurement systems, a flow chart is made of the measurement process.

This would include delivery of the part or sub-system being measured, the measurement itself, and the return of the part or sub-system to the process. Next use some method of brainstorming with the group to develop general criteria for each measurement required. One of the simple methods to use is a cause and effect diagram. A few additional questions to consider in relation to measurement planning: The flow chart and initial discussion will facilitate the identification of the key individuals.

Will the data be used for control, sorting, qualification, etc? The way the measurement will be used can change the sensitivity level of the measurement system. What is the product specification? What is the expected process variability? How much of a difference between parts will the gage need to detect? Who will do the training?

Will it be done manually, on a moving conveyor, off-line, automatically, etc? Are the part location and fixturing possible sources of variation? Contact or non-contact? Who will be responsible for the calibration masters? Will the part be clean, oily, hot, etc.? Remember to use data to substantiate common assumptions about the measurement process. It is better to be safe and collect data on the environment, rather than to make decisions based on the wrong information and having a system developed that is not robust to environmental issues.

Current measurement methods should be researched prior to investing in new Research Various equipment. Proven measurement methods may provide more reliable Measurement operation. Where possible, use measurement equipment that has a proven track record. Process Methods. Proposals During and after the fabrication of the measurement equipment and development of the measurement process methods, training, documentation, etc.

These studies and data will be used to understand this measurement process so that this process and future processes may be improved. It has been constructed to be a self-contained discussion about the process of developing a measurement process quotation package, obtaining responses to that package, awarding the project, completing final design, developing the measurement process, and, finally, marrying that measurement process to the production process for which it was created.

To obtain the most benefit from the measurement process, study and address it as a process with inputs and outputs. This chapter was written with the team philosophy in mind. It is not a job description for the downloader or downloading agent.

The activities described here will require team involvement to be completed successfully and it should be administered within the overall framework of an Advanced Product Quality Planning APQP team. This can result in healthy interplay between various team functions — concepts arising out of the planning process may be modified before the gage supplier arrives at a final design that satisfies the measurement system requirements.

The customer and supplier s need to thoroughly understand the project requirements, what the deliverables will be and the methods by which both are to be achieved.

This understanding is derived from accurate timely communication between the two parties. Communication between the customer and the supplier at this time is especially important. Since there may be several levels of concept approvals to be carried out, and possible environmental changes and the potential of team members changing, the measurement process project could falter or even fail.

This risk will be reduced if frequent, detailed communication is maintained and documented between the customer and supplier and formal responsibility an individual for maintaining communication is designated. One method or datum scheme may be required for manufacturing whereas another scheme is required for measurement of the final product measurement. There may be times when a datum scheme used in a final assembly cannot possibly match that used in a sub-component manufacturing process.

When such is the case. During this process. When datum schemes do not match throughout a manufacturing process. Initial responsibility for this may lie with the product design engineer.

After the measurement process has been conceptually designed.. Certain commodities present features which can yield more problems than others. However this should not detract from consideration of these issues with appropriate team members early in the APQP process. The gage supplier will develop a clear appreciation of the overall production process and product usage so that his role is understood not only by him but by others on the team manufacturing. Some may be dictated or heavily implied by the product design.

Gage Source Selection Process Develop the Quotation Package Detailed Engineering Before a measurement process request for quotation package can be supplied to a potential supplier for formal proposals. It is assumed that the gage supplier will be involved with the APQP process. This can be part of the APQP team. To better develop this concept.

The team may research various issues to help decide which direction or path will be followed for designing the measurement process. Other concepts may require the expertise of the gage source. The team of individuals that will employ and be responsible for the maintenance and continual improvement of the measurement process have direct responsibility for developing the detailed concept.

This may be driven by the complexity of the measurement system and a team decision as to what makes sense. Before a customer asks a supplier to suggest solutions to process problems.

Acceptable standards may be considered in two categories: Preventive lubrication. Simple analytical methods run charts. Conducting preventive maintenance on a stable system.

What activities should be scheduled for preventive maintenance e. These guidelines serve to communicate acceptable standards. Then and only then will the process be properly used. Maintenance Much of these activities will depend on the complexity of the measurement system. Many activities. Simpler gages may require only an inspection Considerations at regular intervals.

Data collection methods and maintenance recommendations related to these activities can be obtained from the original manufacturer. Specifications serve as guidelines for both the customer and supplier in the Specifications design and build process. Cost issues may affect the format. In fact this is preferable and improves advanced measurement planning and costs. After the measurement process is implemented and in use.

Planning preventive maintenance activities should coincide with the initiation of the measurement process planning. It may involve engineering standards chosen from those of the OEM. Certain items can be noted: C An exceptional condition could be a significant disparity with O regard to price or delivery — this would not necessarily be N Q C U discounted as a negative factor — one supplier may have discovered E O an item that others overlooked.

If duplicate fixtures or systems are required. Design standards will detail the method of communicating the design CAD — e. The usual strategy behind documentation is to provide an original set of mechanical and electrical designs CAD or hardcopy drawings for the measurement process hardware at the time of delivery.

The OEM may require the use of particular standards at either the design or build phase and may even require formal approvals before the measurement system may be released for use. Build tolerance should be based on a combination of the capabilities of the process used to produce the gage or gage component.

As quotations are received. Use of standard ized components or subassemblies also leads to interchangeability. Build tolerance should not be a mere given percent of product tolerance alone.. The required format of the final design may be some form of computer assisted design CAD or hardcopy engineering drawings.

This may satisfy initial implementation requirements. Build standards will cover the tolerances to which the measurement system must be built. It may also cover performance standards for a more complex measurement system. T Documentation is sometimes overlooked when acquiring a measurement process.

A complete documentation package may include: It provides the user with possible alternative routes to reach the desired destinations troubleshooting guides or diagnostic trees if the main route is blocked or closed.

For example.. And it should never be used. The Numbers Should Add to I learned early in math that percentages of a total should add to What is happening? He shows the trigonometric functions that give rise to the percentage values above.

The percentages listed above are not proportions. But the fact that they are listed as percentages gives the impression that they are. The major reason is that standard deviations are not additive. Have operators take measurements. Plot data. Use Average and Range method analysis of variance on data.

Calculate total variance. Obtain a sample 50 and establish its reference value relative to a traceable standard. In this process 3 appraisers are measure each part at 3 times.

Find out the cross tables of two appraiser i. Determine the kappa value for each appraiser. Figure 5. With this new information develop another group of cross-tabulations comparing each appraiser to the reference decision. Also 6. Then calculate the effectiveness of the measurement system.

The method use Vernier caliper These equipment s are Vernier caliper and found to be out of limits. So after suggestions on Micro meter. After the improvement we again calculate appraiser variation improvement i. The improvement done for of equipment ,the total variation of equipment s make system is acceptable are: were reduced. Ergonomics of working space may be improved Dial Gauge 1. Solapur Maharashtra. Appraiser2 Effectiveness Miss False alarm [3] Georgia A.Observed vs Generate random order for operators and parts to complete the run.

If the data quality is low.

DOA from classical beamformer Fig. Such as:-Average and Range method including the Control Chart method. Careful consideration needs to be given to the material s selected for a standard.

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